Physicians now commonly enlist imaging methods that completely or partially detect internal body structures of a patient. These methods include, for example, computer tomography, nuclear spin (MR) tomography, PET and SPECT methods, and x-ray methods. The internal body structures detected by the imaging method, with the aid of a computer, can be output as sectional images or also as a three-dimensional reconstruction. Such an image output significantly aids the physician in analyzing and classifying the individual structures in the interior of the patient's body.
Sometimes, however, some of the cited methods are unable to exactly and/or completely delineate individual structures from each other. This can occur particularly when two different structures yield the same contrast value and/or color value. It is then not always possible, and also very expensive, to delineate such structures by means of another imaging method. As a result, reference atlases are then adduced which contain typical shapes of internal structures for particular parts of the body as they would appear in particular imaging methods.
If, for example, a portion of the delineation of a certain body structure from the imaging method with respect to its surroundings is already available, but another portion is not, then a mapping function can be ascertained from the available portion of the delineation in the body structure image data set and a corresponding portion of a reference data set (e.g., the atlas). The mapping function can map the corresponding parts of the reference data set onto the parts of the body structure image data set. If this mapping function is then available, then the delineations and/or physical features that cannot be gathered directly from the body structure image data set can be obtained from the reference data set, e.g., by applying the mapping function to the reference data set. EP 1 363 242 A1 describes such a method, in which a mapped reference label data set is also used to generate an individualized label data set by superimposing it with the patient data set.
The mappings used in such methods include global elastic deformation (e.g., an entire body structure, even if it consists of individual parts, is elastically deformed as a reference data set, such that it is adapted to the actual body structure image data set). The resulting match, for example, then can be used to delineate and visually highlight structures in the body structure image data set (patient data set). This process also is referred to as segmenting, or, because reference data set atlases are used, “atlas segmenting” or “atlas segmentation”. This atlas segmenting, when mapping, also can take into account global shifts in the entire structure.
In some applications, however, such a procedure as described above has not been successful. This is particularly true where structures comprise a number of separate constituents. In such instances, segmenting may be unstable or it may not work at all.